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BIOGRAPHICAL SKETCH Garrett M. Fitzmaurice Associate Professor Of

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Principal Investigator/Program Director (Last, First, Middle):

BIOGRAPHICAL SKETCH

Provide the following information for the key personnel and other significant contributors in the order listed on Form Page 2.

Follow this format for each person. DO NOT EXCEED FOUR PAGES.

  • NAME
  • POSITION TITLE

  • Garrett M. Fitzmaurice
  • Associate Professor of Biostatistics

eRA COMMONS USER NAME

EDUCATION/TRAINING (Begin with baccalaureate or other initial professional education, such as nursing, and include postdoctoral training.)

DEGREE

  • INSTITUTION AND LOCATION
  • YEAR(s)
  • FIELD OF STUDY

(if applicable)

BA, MA MSc

  • National University of Ireland
  • 1983, 1987

1986
Psychology
University of London Harvard University
Quantitative Methods

  • Biostatistics
  • ScD
  • 1993

Professional Experience:

1986-1989 1989-1990 1990-1993 1993-1994 1994-1997 1997-1999
Statistician, Department of Psychology, New York University Teaching Assistant, Department of Biostatistics, Harvard School of Public Health Teaching Fellow in Biostatistics, Department of Biostatistics, Harvard SPH Post-doctoral Research Fellow, Department of Biostatistics, Harvard SPH Research Fellow, Nuffield College, Oxford University, United Kingdom Assistant Professor of Biostatistics, Harvard School of Public Health
1999-present Associate Professor of Biostatistics, Harvard School of Public Health 2004-present Associate Professor of Medicine (Biostatistics), Harvard Medical School 2004-present Biostatistician, Division of General Medicine, Brigham and Women’s Hospital, Boston 2006-present Foreign Adjunct Professor of Biostatistics, Karolinska Institute, Sweden

Honors and Awards:

1991 1991,1993 1992
Harvard School of Public Health Alumni Scholarship Harvard School of Public Health Teaching Assistant Award Biometrics Society (ENAR) Student Paper Award

  • ASA Biometrics Section Student Paper Award
  • 1992

2002 2003
Elected Member of the International Statistical Institute Elected Fellow of the American Statistical Association
1998-present Statistics Editor: Nutrition 1998-2003 1999-2002
Associate Editor: Journal of the Royal Statistical Society, Series B Associate Editor: Biostatistics
2005-present Associate Editor: Biometrics

B. Selected peer-reviewed publications (in chronological order).

1. Fitzmaurice GM and Laird NM. A likelihood-based method for analysing longitudinal binary responses.
Biometrika, 1993; 80:141-151.
2. Fitzmaurice GM, Laird NM and Rotnitzky A. Regression models for discrete longitudinal responses (with discussion). Statistical Science, 1993; 8:284-309.

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Biographical Sketch Format Page

Principal Investigator/Program Director (Last, First, Middle):

Farmer, Paul Edward
3. Fitzmaurice GM, Laird NM and Lipsitz SR. Analysing incomplete longitudinal binary responses: A likelihood-based approach. Biometrics, 1994; 50:601-614.
4. Lipsitz SR, Fitzmaurice GM, Orav EJ and Laird NM. Performance of generalized estimating equations in practical situations. Biometrics, 1994; 50:270-78.
5. Fitzmaurice GM and Lipsitz SR. A model for binary time series data with serial odds ratio patterns. Applied

Statistics, 1995; 44:51-61.

6. Fitzmaurice GM. A caveat concerning independence estimating equations with multivariate binary data.
Biometrics, 1995; 51:309-317.
7. Fitzmaurice GM, Molenberghs G and Lipsitz SR. Regression models for longitudinal binary responses with informative drop-outs. J. R. Statist. Soc. Series B, 1995; 57:691-704.
8. Fitzmaurice GM and Laird NM. Regression models for a bivariate discrete and continuous outcome with

clustering. J.   Amer. Statist. Assoc., 1995; 90:845-852.

9. Fitzmaurice GM, Laird NM, Zahner GEP and Daskalakis C. Bivariate logistic regression analysis of childhood psychopathology ratings using multiple informants. Amer. J. Epidemiology, 1995; 142:1194- 1203.
10. Fitzmaurice GM, Heath AF and Clifford P. Logistic regression models for binary panel data with attrition. J.

R. Statist. Soc. Series A, 1996; 159:249-263.

11. Fitzmaurice GM, Laird NM and Zahner GEP. Multivariate logistic models for incomplete binary responses.

J. Amer. Statist. Assoc., 1996; 91:99-108.

12. Fitzmaurice GM. Model selection with overdispersed data. The Statistician, 1997; 46:1-11. 13. Fitzmaurice GM and Laird NM. Regression models for mixed discrete and continuous responses with potentially missing values. Biometrics. 1997; 53:110-122.
14. Lipsitz SR, Fitzmaurice GM, Molenberghs G and Zhao LP. Quantile regression models for longitudinal data with drop-outs. Applied Statistics. 1997; 46:463-476.
15. Fitzmaurice GM, Heath AF and Cox DR. Detecting overdispersion in large-scale surveys: Application to a study of social class and education in Britain (with discussion). Applied Statistics. 1997; 46:415-432.
16. Fitzmaurice GM. Non-ignorable drop-out in longitudinal studies. In: The Encyclopedia of Biostatistics (eds.
P. Armitage and T. Colton). Chichester: Wiley & Sons, 1998.
17. Fitzmaurice GM. Regression models for discrete longitudinal responses. In: Statistical Analysis of Medical
Data: New Developments (eds. B. Everitt and G. Dunn). London: Arnold, 1998.
18. Lipsitz SR, Ibrahim JG and Fitzmaurice GM. Likelihood methods for incomplete longitudinal binary responses with incomplete categorical covariates. Biometrics, 1999; 55:214-223.
19. Laird NM, Fitzmaurice GM and Schwartz AG. The analysis of case-control data: Epidemiologic studies of

familial aggregation. Handbook of Environmental and Public Health Statistics. 2000; 465-482.

20. Fitzmaurice GM and Laird NM. Generalized linear mixture models for handling nonignorable dropouts in longitudinal studies. Biostatistics, 2000; 1:141-156.
21. Fitzmaurice GM, Lipsitz, SR, Molenberghs G and Ibrahim JG. Bias in estimating association parameters for longitudinal binary responses with drop-out. Biometrics, 2000; 56:528-536.
22. Fitzmaurice GM, Laird NM and Shneyer L. An alternative parameterization of the general linear mixture model for longitudinal data with non-ignorable dropouts. Statistics in Medicine, 2001; 20:1009-1021.
23. Fitzmaurice GM. A conundrum in the analysis of change. Nutrition, 2001; 17:360-361. 24. Goldwasser MA and Fitzmaurice GM. Multivariate linear regression analysis of childhood psychopathology

using multiple informant data. International Journal of Methods in Psychiatric Research, 2001; 10:1-10.

25. Fitzmaurice GM and Laird NM. Logistic regression. In: The International Encyclopedia of the Social and
Behavioral Sciences (eds. N. Smelser and P. Baltes). New York: Elsevier, 2001.

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Continuation Format Page

Principal Investigator/Program Director (Last, First, Middle):

Farmer, Paul Edward
26. Birmingham J and Fitzmaurice GM. A pattern-mixture model for longitudinal binary responses with nonignorable nonresponse. Biometrics, 2002; 58:989-996.
27. Birmingham J, Rotnitzky A and Fitzmaurice GM. Pattern-mixture and selection models for analyzing longitudinal data with monotone missing patterns. J Roy Stat Soc B, 2003; 65(1):275-297.
28. Horton NJ and Fitzmaurice GM. Maximum likelihood estimation of bivariate logistic regression models for incomplete responses with indicators of ignorable and non-ignorable missingness. Applied Statistics, 2003; 51(3):281-295.
29. Fitzmaurice GM. Methods for handling dropouts in longitudinal clinical trials. Stat Neer, 2003; 57:75-99. 30. O'Brien LM and Fitzmaurice, GM. Analysis of longitudinal multiple-source binary data using generalized estimating equations. J Roy Stat Soc C-App, 2004; 2004; 53:177-193.
31. Fitzmaurice GM, Laird NM, Ware JH. Applied Longitudinal Analysis. New Jersey: Wiley, 2004. 32. Fitzmaurice GM. Adjusting for confounding. Nutrition 2004, 20; 594-596. 33. Lipsitz SR, Parzen M, Ibrahim JG, Natarajan S, Fitzmaurice GM. Generalized linear models with a coarsened covariate. J Roy Stat Soc C-App, 2004; 53:279-292.
34. Horton NJ and Fitzmaurice GM. Regression analysis of multiple source data from complex survey samples.
Statistics in Medicine 2004; 23, 2911-2933.
35. O’Brien LM and Fitzmaurice GM. Regression models for the analysis of longitudinal Gaussian data from multiple sources. Statistics in Medicine 2005, 24, 1725-1744.
36. Liu I-C, Xu RX, Blacker DL, Fitzmaurice GM, , Lyons MJ, Tsuang MT. The application of a random effects model to censored twin data. Behavior Genetics 2005, 35, 781-789.
37. Fitzmaurice GM, Lipsitz SR, Molenberghs G, Ibrahim JG. A protective estimator for longitudinal binary data with non-ignorable non-monotone missingness. J. R. Statist. Soc. Series A 2005; 168, 723-735.
38. Huang W and Fitzmaurice GM. Analysis of unbalanced longitudinal data. J Roy Stat Soc B, 2005; 67:135-
155.
39. Parzen M, Lipsitz SR, Fitzmaurice GM. A note on reducing the bias of the approximate Bayesian bootstrap imputation variance estimator. Biometrika 2005, 92, 971-974.
40. Baker SG, Fitzmaurice GM, Freedman LS, Kramer BS. Simple adjustments for randomized trials with missing or censored outcomes arising from informative covariates. Biostatistics 2006, 7, 29-40.
41. Wilkins K and Fitzmaurice GM A hybrid model for non-ignorable dropout in longitudinal binary responses

Biometrics 2006, In Press.

42. Fitzmaurice GM, Lipsitz SR, Ibrahim JG, Gelber R and Lipshultz S (2006). Estimation in regression models for longitudinal binary data with outcome-dependent follow-up. Biostatistics 2006, In Press.

C. Research Support. List selected ongoing or completed (during the last three years)

5 R01 GM29745 (PI: Garrett Fitzmaurice) NIH/NIGMS
9/1/81- 1/31/06
Methods for Analysis of Longitudinal Data The major goals of this project are to research and develop statistical methodology for the analysis of longitudinal and repeated measures data.

Dr. Fitzmaurice has been directing the research activities of this grant that focuses on the development of statistical methods for handling informative dropouts with discrete longitudinal data using pattern-mixture modeling approaches.

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  • Understanding the Space of Research

    Understanding the Space of Research

    Biostatistics and Biometrics Open Access Journal ISSN: 2573-2633 Review Article Biostat Biometrics Open Acc J Volume 4 Issue 4 - January 2018 Copyright © All rights are reserved by Dhritikesh C DOI: 10.19080/BBOAJ.2018.04.555642 Understanding the Space of Research Dhritikesh C* Department of Statistics, Handique Girls’ College, India Submission: October 20, 2017; Published: January 22, 2018 *Corresponding author: Dhritikesh Chakrabarty, Department of Statistics, Handique Girls’ College, India Email: Abstract The theory of research, the history of the beginning of whose development was lost in the dust of antiquity, has been found to be the vital player in playing the role of developing knowledge everywhere. At the current stage of human civilization, research has become an unavoidable activity but also a partner/helper for most of the problems in the society. A journey has been made for understanding the space of research and essential component of each and every branch/field of academic world. The research is not only an unavoidable component of academic specifically on the meaning of research, definition of research, characteristics of research, methodology of research, types of research etc. This paperKeywords: is based Research; on some Research of the findings process; obtained Characteristics; in the study. Methodology; Types Meaning and Definition of Research Dictionary definitions o Research is a detailed study of a subject, especially in order to discover (new) information or reach a (new) o To search or investigate exhaustively. understanding. o Studious inquiry or examination; especially: o The word “research” is used to describe a number of investigation or experimentation aimed at the discovery and similar and often overlapping activities involving a search interpretation of facts, revision of accepted theories or laws for information.